Microsoft and IBM Trade AI, Machine Learning Volleys

The next generation of computing will be marked by advances in machine learning and artificial intelligence, and old-guard tech companies like Microsoft and IBM are vying to establish their place in it.

At this week's World of Watson conference, IBM unveiled a new Watson Data Platform and launched the Watson Machine Learning Service, among a host of other announcements. Microsoft, meanwhile, stole some of Big Blue's thunder by releasing an updated Microsoft Cognitive Toolkit for "deep learning."

Incidentally, these announcements were made just one day before research firm IDC issued a release titled, "Worldwide Cognitive Systems and Artificial Intelligence Revenues Forecast to Surge Past $47 Billion in 2020." That gives an indication of the kind of stakes that IBM, Microsoft and other leaders are competing for.

Here's a look at each company's efforts this week.

Microsoft Cognitive Toolkit
The Microsoft Cognitive Toolkit is described as "a free, easy-to-use, open source, commercial-grade toolkit that trains deep learning algorithms to learn like the human brain." Sporting an update announced Tuesday, it joins other advanced computing initiatives like Microsoft's Cognitive Services APIs , used by developers to integrate speech, language, knowledge and search APIs into their apps.

Microsoft said the toolkit is used by developers for its deep learning functionality, for which it provided the following definition in a blog post: "Broadly speaking, deep learning is an artificial intelligence technique in which developers and researchers use large amounts of data -- called training sets -- to teach computer systems to recognize patterns from inputs such as images or sounds."

Being able to work on multiple servers and harness the computing power of GPUs as well as CPUs, it helps advances in speech and image recognition, search relevance and other areas.

"For example, a deep learning system can be given a training set showing all sorts of pictures of fruits and vegetables, after which it learns to recognize images of fruits and vegetables on its own," Microsoft said. "It gets better as it gets more data, so each time it encounters a new, weird-looking eggplant or odd-shaped apple, it can refine the algorithm to become even more accurate."

Updates to the toolkit, which is available on GitHub featuring its old CNTK name, include new support for Python and C++ that was added to address developer feedback.

Microsoft said advances in deep learning, along with the availability of increasing computing power, have led to research milestones and commercial products such as Skype Translator, which can recognize a user's speech and provide real-time voice translation, and the Cortana digital assistant, which also can understand a user's voice and provide assistance for tasks such as searching or remembering appointments.

IBM Watson Data Platform
Speaking of democratization, IBM is working toward the same thing with Tuesday's unveiling of the IBM Watson Data Platform.

"Machine learning is incredibly powerful, but many of today's data professionals lack the skills to fully exploit it for business and the ability to effectively collaborate on datasets," said Bob Picciano, senior vice president of IBM Analytics, in a statement. "Watson Data Platform applies cognitive assistance for creating machine learning models, making it far faster to get from data to insight. It also, provides one place to access machine learning services and languages, so that anyone, from an app developer to the Chief Data Officer, can collaborate seamlessly to make sense of data, ask better questions, and more effectively operationalize insight."

IBM said the platform brings to market the company's previous AI-powered decision-making platform in the company's cloud, Project DataWorks.

The platform provides greater collaboration among developers, data scientists, data engineers and business analysts, IBM said, letting them easily work together on one dataset using whatever tools and languages -- including SQL, Python, R, Java and Scala -- they prefer, while also easily sharing analytics insights and visualizations across an organization.

The company said the platform provides these data professionals with the following abilities:

Ingest large volumes of diverse data into the cloud at record speeds -- at more than 100 gigabytes per second.

Cleanse, edit and shape data for easier modeling.

Add and remove collaborators as needed while maintaining version control.

Drag and drop services into analytic notebooks for better productivity and time management.

IBM also made available its IBM Watson Machine Learning Service, which it said simplifies machine learning with an intuitive, self-service interface. Available on the company's Bluemix hybrid cloud development platform, this was previously called the IBM Predictive Analytics service.

"Built on Apache Spark, Watson Machine Learning intelligently and automatically builds models from structured and unstructured data and open machine learning libraries, while accelerating model deployment into business operations," IBM said. "Its patented Cognitive Assistance for Data Science technology scores each machine-learning algorithm against the data provided to recommend the best match for the need. It also includes the most comprehensive set of algorithms in the industry."

The company also made several other announcements at its conference this week, including: new cognitive solutions for professionals in marketing, commerce, supply chain and human resources; a partnership with Slack to bring Watson to that service's community of developers; Watson-based educational initiatives and more.